def setUp(self):
self.preprocessor = Processor(
X_imgpath='./tests/data/valid/noise.png',
y_dirpath='./tests/data/test/',
border=1, rnd=rnd)
class TestProcessor(unittest.TestCase):
def setUp(self):
self.preprocessor = Processor(
X_imgpath='./tests/data/valid/noise.png',
y_dirpath='./tests/data/test/',
border=1, rnd=rnd)
def test_sliding_window(self):
x1 = self.preprocessor.get_X_fast()
x2 = self.preprocessor.get_X()
y1 = self.preprocessor.get_y_fast()
y2 = self.preprocessor.get_y()
pass
def test_get_random_patch(self):
patch = self.preprocessor.get_random_patch()
patch2 = self.preprocessor.get_random_patch()
patch3 = self.preprocessor.get_random_patch()
patch = patch[0].flatten()
patch2 = patch2[0].flatten()
patch3 = patch3[0].flatten()
center_index = (len(patch) - 1) / 2
self.assertNotEqual(patch[center_index], patch2[center_index])
self.assertNotEqual(patch[center_index], patch3[center_index])
self.assertNotEqual(patch2[center_index], patch3[center_index])
def test_fully_random_consistency(self):
self.preprocessor.load_images('./tests/data/train/gradient.png',
'./tests/data/train/')
x, y = self.preprocessor.get_random_patch()
x = x.flatten()
center_index = (len(x) - 1) / 2
self.assertEqual(x[center_index], y)
def test_get_fast_x_consistency(self):
self.preprocessor.load_images('./tests/data/train/gradient.png',
'./tests/data/train/')
x = self.preprocessor.get_X_fast()[:2]
y = self.preprocessor.get_y_fast()[:2]
center_index = (len(x[0]) - 1) / 2
self.assertEqual(x[0][center_index], y[0][0])
self.assertEqual(x[1][center_index], y[1][0])
def test_patchsize_according_bordersize(self):
# The patch has to have (2*border+1)**2 pixels
for border in [3, 4]:
self.preprocessor.set_border(border)
ds = self.preprocessor.get_dataset()
self.assertEqual(len(ds[0][0]), (2*border+1)**2)
def test_patches_amounth(self):
shape = np.array(PIL.Image.open(self.preprocessor.X_imgpath)).shape
num_pixels = shape[0] * shape[1]
num_entires = len(self.preprocessor.get_dataset())
self.assertEqual(num_entires, num_pixels)
def test_center_pixels(self):
# Prepare test image
img_path = self.preprocessor.X_imgpath
img_array = np.array(PIL.Image.open(img_path)).flatten()
img_array = img_array / 255.
# Generate Patches
border = 3
self.preprocessor.set_border(border)
X, y = zip(*self.preprocessor.get_dataset())
center_index = (len(X[0]) - 1) / 2
# The first patch's center pixel must be the first pixel of the image
first_pixel = img_array[0]
first_center_pixel = X[0][center_index]
self.assertEqual(first_center_pixel, first_pixel)
# The next pixel nighbour of the first patch's center pixel
# must be the second pixel of the image
next_pixel = img_array[1]
next_center_pixel = X[0][center_index + 1]
self.assertEqual(next_center_pixel, next_pixel)
# The last patch's center pixel must be the last pixel in the image
last_pixel = img_array[-1]
last_center_pixel = X[-1][center_index]
self.assertEqual(last_center_pixel, last_pixel)
# The previous pixel nighbour of the last patch's center pixel
# must be the second last pixel of the image
second_last_pixel = img_array[-2]
second_last_center_pixel = X[-1][center_index - 1]
self.assertEqual(second_last_center_pixel, second_last_pixel)
def test_y_pixels(self):
name = os.path.basename(self.preprocessor.X_imgpath)
y_imgpath = os.path.join(self.preprocessor.y_dirpath, name)
img_array = np.array(PIL.Image.open(y_imgpath)).flatten() / 255.
border = 1
self.preprocessor.border = border
X, y = zip(*self.preprocessor.get_dataset())
self.assertEqual(y[0], img_array[0])
self.assertEqual(y[len(y) / 2], img_array[len(y) / 2])
self.assertEqual(y[-1], img_array[-1])
